39 Data Discovery and Visualization Buyer’s Guide Easy Data Discovery with Smart Data Transitions Thought Leadership Data Animations and Transitions What does your data communicate? Can you see the correlations and insights hiding in your data? Visual analytics tools that let you explore data, rather than simply view it, result in a better understanding of the underlying data as well as providing opportunities for deeper insights. Smooth, animated data transitions makes interactive data analysis and visualization even easier, allowing users to easily follow data changes and quickly see data correlations and trends. In their visualization study, “Animated Transitions in Statistical Data Graphics,” Jeffrey Heer and George G. Robertson of the University of California, Berkeley (2007) conducted two controlled experiments to assess the efficacy of animated transitions. They found that participants significantly preferred animation over static transitions and that appropriately designed animated transitions significantly improve graphical perception of analysis. Their study provides strong evidence that, “with careful design, animated transitions can improve graphical perception of changes between statistical data graphics.” In their study they noted that, “overall, subjects were highly enthusiastic about animated data graphics, and felt that it facilitated both improved understanding and increased engagement. The vast majority of participants wanted to use animated data graphics in their own analysis and presentation.” Data Discovery and Animation in Data Visualization Data discovery allows you to quickly and easily analyze your data in a meaningful way. Data discovery is typically easier when the data is visualized (rather than when the data is in a tabular display, row by row). The discovery process is powered by interactions such as filter, sort, drill-down/up, zoom, etc. These interactions help you to understand how the data behaves under different scenarios and ultimately enables you to gain insight and draw some conclusions.
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39
Data D
iscovery and Visualization Buyer’s Guide
Easy Data Discovery with Smart Data Transitions
Thought Leadership
Data Animations and Transitions
What does your data communicate? Can you see the correlations and insights hiding in
your data? Visual analytics tools that let you explore data, rather than simply view it, result
in a better understanding of the underlying data as well as providing opportunities for
deeper insights. Smooth, animated data transitions makes interactive data analysis and
visualization even easier, allowing users to easily follow data changes and quickly see data
correlations and trends.
In their visualization study, “Animated Transitions in Statistical Data Graphics,” Jeffrey Heer
and George G. Robertson of the University of California, Berkeley (2007) conducted two
controlled experiments to assess the efficacy of animated transitions. They found that
participants significantly preferred animation over static transitions and that appropriately
designed animated transitions significantly improve graphical perception of analysis. Their
study provides strong evidence that, “with careful design, animated transitions can improve
graphical perception of changes between statistical data graphics.” In their study they noted
that, “overall, subjects were highly enthusiastic about animated data graphics, and felt that
it facilitated both improved understanding and increased engagement. The vast majority of
participants wanted to use animated data graphics in their own analysis and presentation.”
Data Discovery and Animation in Data Visualization
Data discovery allows you to quickly and easily analyze your data in a meaningful way.
Data discovery is typically easier when the data is visualized (rather than when the data
is in a tabular display, row by row). The discovery process is powered by interactions such
as filter, sort, drill-down/up, zoom, etc. These interactions help you to understand how the
data behaves under different scenarios and ultimately enables you to gain insight and draw
some conclusions.
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Data animations enable you to easily convey changes over time or the transitions between
states and help to show a full data process and path where it is difficult to express with static
graphics or text alone. The concept of data animation has been known for a while in the
data visualization space but is often used only for the sake of making the data visualization
look a bit more visually appealing (“sexy”) rather than contributing to the data discovery
process. Oftentimes, users would like to make sure that gauge needles can be animated
just because it looks “cool.” Often after they start using the animation on the visualizations
they “get tired” of those animations as the “cool” effect is not as exciting as it was at first;
now it’s just a waste of time as they need to wait until the animation is done loading the
data so they can see the actual data value. The data transitions in Dundas BI are designed
to allow the user to comprehend each type of change made to a visualization when the
data changes. These real-time, animated changes are readily visible, greatly enhancing data
analysis. Dundas BI data transitions ensure that users quickly understand the relationship
between the current and previous views without effort, see trends more easily, and present
their data more effectively.
Data discovery becomes much smarter with animations and transition changes added to
your data visualization, including
• Change the axes of the chart
• Reorder the data or filter the data
• Change the data or re-visualize the data
Each data transition is independent and allows users to explore and interact for an in-depth
data discovery and analysis.
Dundas BI features a canvas-like environment where users can drag and drop measures,
dimensions, or predefined metric sets and then customize for discovery. The visual discovery
environment within Dundas BI includes an intuitive drag-and-drop dashboard designer to
provide visual data discovery. To make visualizations more immediately explorable, the “Re-
visualize” button and visualizations menu in Dundas BI provides the ability for users to sort,
filter, and drill up and down, with best-practice animations that visually show the user the
impact of changing dimensions within visualization outputs.
Data transitions can readily support your data discovery by helping you better understand the effect of the interaction you applied to your data. ”
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iscovery and Visualization Buyer’s Guide
How Data Transitions Enable Data Discovery
At Dundas we believe that data transitions, if applied correctly can do much more than
just add cool effects to your data visualizations. Data transitions can readily support your
data discovery by helping you better understand the effect of the interaction you applied
to your data. A well-known example is the illustration by Hans Rosling of “200 Years That
Changed the World.” In this example, Rosling uses interactive animations to visualize
how all the countries of the world have developed since 1809, showing the change in life
expectancy and income per person over the last two centuries. Rosling demonstrates how
moving the data points over time can help the user better understand the trend changes
that may be too complex to spot compared to a single image or a series of static images.
See 200 Countries, 200 Years, 4 Minutes.
Data Transitions in Dundas BI
In Dundas BI, transitions are built-in and designed to easily allow the user to identify and
comprehend each type of change made to a visualization when the data changes. Data
transitions are applied by default on any data interaction users may apply. Each interaction
will drive a transition that helps the user better understand the data changes he/she just
triggered, for example, a drill down. A drill down breaks the data into distinct categories.
For example, when the user selects a certain time period and point showing data at the
quarter level and wants to drill down to see the data at the month level, instead of having
the chart show the data across all the months of the selected quarter at once or using a
random animation, Dundas BI chart is using smart transition that will display the changes
to the user in stages:
Stage 1: The user notices that higher number in the third quarter and wants to drill down
into it to break it down.
Stage 2: The user will notice the data points change by having all the non-selected quarter
data points disappear and having the selected quarter data point split into 3 different
points (one for each month of that quarter). This helps the user notice what the selected
data points represent (in this case 3 different months).
Stage 3: The axis range will now change to reflect the appropriate range of the new data
points (the 3 months). This is important as the user may start by viewing data at the one
level that could, for example, range in the millions and then drill down into another level
that ranges in the thousands. Having the transition done in stages rather than at once will
help the user notice the range change and better grasp the magnitude of the data points.
A good data visualization will let you interact directly with that data, drill down into its details, see it from multiple perspectives, and draw your own conclusions. ”